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wf-composer

Semantic workflow composer — parse natural language workflow description into a DAG of skill/CLI/agent nodes, auto-inject checkpoint save nodes, confirm with user, persist as reusable JSON template. Triggers on "wf-composer " or "/wf-composer".

Quellinformationen

Repository
catlog22/Claude-Code-Workflow
Letzte Quellaktivität
17. März 2026 um 15:03
Erkannte Sprache von SKILL.md
Englisch
Sterne
2.131
Forks
166

Installationsoptionen

Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.

Quelldateien prüfen

Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.

Datei-Explorer
8 Dateien

SKILL.md wird angezeigt

SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau
name
wf-composer
description
Semantic workflow composer — parse natural language workflow description into a DAG of skill/CLI/agent nodes, auto-inject checkpoint save nodes, confirm with user, persist as reusable JSON template. Triggers on "wf-composer " or "/wf-composer".
argument-hint
[workflow description]
allowed-tools
Agent(*), AskUserQuestion(*), Read(*), Write(*), Edit(*), Bash(*), Glob(*), Grep(*)
# Workflow Design Parse user's semantic workflow description → decompose into nodes → map to executors → auto-inject checkpoints → confirm pipeline → save as reusable `workflow-template.json`. ## Architecture ``` User describes workflow in natural language -> Phase 1: Parse — extract intent steps + variables -> Phase 2: Resolve — map each step to executor (skill/cli/agent/command) -> Phase 3: Enrich — inject checkpoint nodes, set DAG edges -> Phase 4: Confirm — visualize pipeline, user approval/edit -> Phase 5: Persist — save .workflow/templates/<name>.json ``` ## Shared Constants | Constant | Value | |----------|-------| | Session prefix | `WFD` | | Template dir | `.workflow/templates/` | | Template ID format | `wft-<slug>-<date>` | | Node ID format | `N-<seq>` (e.g. N-001), `CP-<seq>` for checkpoints | | Max nodes | 20 | ## Entry Router Parse `$ARGUMENTS`. | Detection | Condition | Handler | |-----------|-----------|---------| | Resume design | `--resume` flag or existing WFD session | -> Phase 0: Resume | | Edit template | `--edit <template-id>` flag | -> Phase 0: Load + Edit | | New design | Default | -> Phase 1: Parse | ## Phase 0: Resume / Edit (optional) **Resume design session**: 1. Scan `.workflow/templates/design-drafts/WFD-*.json` for in-progress designs 2. Multiple found → AskUserQuestion for selection 3. Load draft → skip to last incomplete phase **Edit existing template**: 1. Load template from `--edit` path 2. Show current pipeline visualization 3. AskUserQuestion: which nodes to modify/add/remove 4. Re-enter at Phase 3 (Enrich) with edits applied --- ## Phase 1: Parse Read `phases/01-parse.md` and execute. **Objective**: Extract structured semantic steps + context variables from natural language. **Success**: `design-session/intent.json` written with: steps[], variables[], task_type, complexity. --- ## Phase 2: Resolve Read `phases/02-resolve.md` and execute. **Objective**: Map each intent step to a concrete executor node. **Executor types**: - `skill` — invoke via `Skill(skill=..., args=...)` - `cli` — invoke via `ccw cli -p "..." --tool ... --mode ...` - `command` — invoke via `Skill(skill="<namespace:command>", args=...)` - `agent` — invoke via `Agent(subagent_type=..., prompt=...)` - `checkpoint` — state save + optional user pause **Success**: `design-session/nodes.json` written with resolved executor for each step. --- ## Phase 3: Enrich Read `phases/03-enrich.md` and execute. **Objective**: Build DAG edges, auto-inject checkpoints at phase boundaries, validate port compatibility. **Checkpoint injection rules**: - After every `skill` → `skill` transition that crosses a semantic phase boundary - Before any long-running `agent` spawn - After any node that produces a persistent artifact (plan, spec, analysis) - At user-defined breakpoints (if any) **Success**: `design-session/dag.json` with nodes[], edges[], checkpoints[], context_schema{}. --- ## Phase 4: Confirm Read `phases/04-confirm.md` and execute. **Objective**: Visualize the pipeline, present to user, incorporate edits. **Display format**: ``` Pipeline: <template-name> ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ N-001 [skill] workflow-lite-plan "{goal}" | CP-01 [checkpoint] After Plan auto-continue | N-002 [skill] workflow-test-fix "--session N-001" | CP-02 [checkpoint] After Tests pause-for-user ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Variables: goal (required) Checkpoints: 2 (1 auto, 1 pause) ``` AskUserQuestion: - Confirm & Save - Edit node (select node ID) - Add node after (select position) - Remove node (select node ID) - Rename template **Success**: User confirmed pipeline. Final dag.json ready. --- ## Phase 5: Persist Read `phases/05-persist.md` and execute. **Objective**: Assemble final template JSON, write to template library, output summary. **Output**: - `.workflow/templates/<slug>.json` — the reusable template - Console summary with template path + usage command **Success**: Template saved. User shown: `Skill(skill="wf-player", args="<template-path>")` --- ## Specs Reference | Spec | Purpose | |------|---------| | [specs/node-catalog.md](specs/node-catalog.md) | Available executors, port definitions, arg templates | | [specs/template-schema.md](specs/template-schema.md) | Full JSON template schema |
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